5 citations · 8 across the 4 of their papers we have counts for
4 papers
Breaking Alignment Barriers: TPS-Driven Semantic Correlation Learning for Alignment-Free RGB-T Salient Object Detection
Lupiao Hu, Fasheng Wang, Fangmei Chen +2
Existing RGB-T salient object detection methods predominantly rely on manually aligned and annotated datasets, struggling to handle real-world scenarios with raw, unaligned RGB-T i…
ST-SAM: SAM-Driven Self-Training Framework for Semi-Supervised Camouflaged Object Detection
Xihang Hu, Fuming Sun, Jiazhe Liu +2
Semi-supervised Camouflaged Object Detection (SSCOD) aims to reduce reliance on costly pixel-level annotations by leveraging limited annotated data and abundant unlabeled data. How…
Beyond Whole Dialogue Modeling: Contextual Disentanglement for Conversational Recommendation
Guojia An, Jie Zou, Jiwei Wei +3
Conversational recommender systems aim to provide personalized recommendations by analyzing and utilizing contextual information related to dialogue. However, existing methods typi…
Behavior-Contextualized Item Preference Modeling for Multi-Behavior Recommendation
Mingshi Yan, Fan Liu, Jing Sun +3
In recommender systems, multi-behavior methods have demonstrated their effectiveness in mitigating issues like data sparsity, a common challenge in traditional single-behavior reco…